In [ ]:
%%time
print(datetime.datetime.now())
print('Maps score KR: fig')
# Load data2plot
savedfile = dirout + 'data2plot-maps-score-KR-'+grid+'.pckl'
with open(savedfile, 'rb') as f1: data2plot = pickle.load(f1)
print("File loaded: "+savedfile)
zfact = 1e6*3600*24 # kmol/m2/s -> mmol/m2/d
#-----------------
# FIGURE PARAM
#-----------------
cm2in = 1/2.54 # converting factor cm to inch
xfsize, yfsize = 4, 3
nrow = len(model_list)
ncol = len(simu_list)
ccrsproj = ccrs.Robinson(central_longitude=-155)
fig, ax = plt.subplots(nrow, ncol, figsize=(xfsize*ncol,yfsize*nrow),
subplot_kw=dict(projection=ccrsproj),
squeeze = False)
######################
# Maps
######################
#-----------------
# CREATE CUSTOM CMAP
#-----------------
from matplotlib.colors import ListedColormap
from matplotlib import cm
cmap = cm.get_cmap('viridis', 256)
newcolors = cmap(np.linspace(0, 1, 10+1))
cmap = ListedColormap(newcolors[1:])
cmap.set_under(color=newcolors[0])
cmap.set_over(color='silver')
#-----------------
# KEYWORDS DICT
#-----------------
kwmap = {'vmin':0, 'vmax':1, 'cmap':cmap, \
'transform':ccrs.PlateCarree() }
kwscatter = dict(edgecolor='k', facecolor='lightgray', alpha = .8, s=60, \
transform=ccrs.PlateCarree())
#---------------------
# Plot score maps
#---------------------
irow = 0
for model in model_list:
icol = 0
for simu in simu_list:
zax = ax[irow, icol]
X = data2plot['maps'][model][simu]['X']
Y = data2plot['maps'][model][simu]['Y']
Z = data2plot['maps'][model][simu]['Z']
pcm = zax.pcolormesh(X, Y, Z, **kwmap)
zax.set_title(model+', '+simu.upper())
zax.coastlines()
# gl = zax.gridlines(crs=ccrs.PlateCarree(), linewidth=1)
# Add point
if model == model4ts:
jj, ii = gridpt[0], gridpt[1]
zax.scatter(X[jj, ii], Y[jj, ii], **kwscatter)
#
icol+=1
#
irow+=1
#
fig.tight_layout()
#---------------------
# Repositionning axes
#---------------------
for irow, axrow in enumerate(ax[1:]):
for icol, zax in enumerate(axrow):
zw1 = zax.get_position()
ny0 = zw1.y0 + (irow+1)*0.35*zw1.height
zax.set_position([zw1.x0, ny0, zw1.width, zw1.height])
#
#
#---------------------
# Colorbar
#---------------------
zw1 = ax[0, 1].get_position()
zw2 = ax[0, 2].get_position()
nx0 = zw1.x0
ny0 = zw1.y1 + .5*zw1.height
nw = zw2.x1 - nx0
nh = 0.03*nw
cax = fig.add_axes([nx0, ny0, nw, nh])
cbar = fig.colorbar(pcm, cax=cax, orientation='horizontal', \
ticklocation='top', extend='both')
cbar.set_label(r'Score of the Kernel Regression')
######################
# Time series
######################
#-----------------
# KEYWORDS DICT
#-----------------
kwtruth = dict(ls='-' , label='Truth' , color='k')
kwkr = dict(ls='--', label='KR' , color='orange')
kwstd = dict(label='$\pm$ std' , color='silver')
kwref = dict(ls='--', label='Ref.' , color='royalblue')
kwbbox = dict(boxstyle ="round", fc ="0.8")
#---------------------
# Plot timeseries
#---------------------
axts = []
for isimu, vsimu in enumerate(simu_list):
zw1 = ax[-1, isimu].get_position()
nx0 = zw1.x0+.1*zw1.width
ny0 = zw1.y0 - 1.3*zw1.height
nw = .8*zw1.width
nh = .9*zw1.height
zax = fig.add_axes([nx0, ny0, nw, nh])
axts.append(zax)
istart = -5*12
X = data2plot['timeseries'][vsimu]['time'] [istart:]
Yref = zfact*data2plot['timeseries'][vsimu]['Ref'] [istart:]
Ykr = zfact*data2plot['timeseries'][vsimu]['KR'] [istart:]
Ykrsup = zfact*data2plot['timeseries'][vsimu]['KRsup'][istart:]
Ykrinf = zfact*data2plot['timeseries'][vsimu]['KRinf'][istart:]
Ytruth = zfact*data2plot['timeseries'][vsimu]['Truth'][istart:]
lltruth, = zax.plot(X, Ytruth, **kwtruth)
llref, = zax.plot(X, Yref , **kwref)
llstd = zax.fill_between(X, Ykrinf, Ykrsup, **kwstd)
llkr, = zax.plot(X, Ykr , **kwkr)
zax.set_xlabel('Years')
zax.set_ylabel('[mmol$\,$C$\,$m$^{-2}\,$d$^{-1}$]')
X = data2plot['maps'][model4ts][simu]['X']
Y = data2plot['maps'][model4ts][simu]['Y']
jj, ii = gridpt[0], gridpt[1]
yyy, xxx = Y[jj, ii], X[jj, ii]
if yyy < 0: lat='%.f°S'%(-yyy)
else : lat='%.f°N'%(yyy)
if xxx < 0: lon='%.f°W'%(-xxx)
else : lon='%.f°E'%(xxx)
zax.set_title(r'Sea-air CO$_2$ flux'+'\n'+model4ts+', '+lon+', '+lat)
#
zax.legend(handles=[lltruth, llref, llkr])
#---------------------
# Save figure
#---------------------
fignam = 'maps-score-KR-'+grid+'.png'
fig.savefig(dirout+fignam, bbox_inches='tight')
print('Figure saved: '+fignam)
# 35s
2023-06-21 15:49:02.177922 Maps score KR: fig File loaded: dimred-220602-score-analysis/data2plot-maps-score-KR-360x180.pckl Figure saved: maps-score-KR-360x180.png CPU times: user 1min 47s, sys: 1.02 s, total: 1min 48s Wall time: 1min 48s
